Perceptions of female business owners in AI

How Women’s Unique Evaluation Of AI Tools Influences Corporate Culture: “When it comes to adopting AI tools at work, studies have shown that men are more likely to experiment with these tools, while women tend to hesitate. That doesn't mean women are less tech-savvy or less open to innovation. It often means they're asking different questions. And those questions reveal something important about how corporate culture is being shaped in the AI era. Women in the workplace are not saying AI is bad. They’re not rejecting it outright. What they’re doing is pausing. They’re questioning how it works, who created it, what data it was trained on, and whether it could be misused. In many cases, they're also concerned about how others will perceive their use of it. Will they look like they're cutting corners? Will the tool reinforce bias? Will their job become obsolete? That kind of hesitation is discernment and the careful weighing of trade-offs. And it reflects a kind of emotional intelligence and long-term thinking that often gets undervalued in tech conversations. Companies that ignore these perspectives risk designing workflows, cultures, and even ethics policies that leave people behind. If you have a team where the loudest voices are the ones who embrace new tools quickly, and quieter voices are the ones raising concerns, you need to ask yourself: are you hearing the full story? Women may not be the early adopters of every AI tool, but they’re often the first to see unintended consequences. They may be the first to notice that the chatbot is reinforcing stereotypes, or that an AI-powered hiring tool is filtering out qualified candidates based on biased data, which are culture-shaping concerns. I've interviewed hundreds of executives, and the best ones aren't the people who jump on every new technology as soon as it hits the market. They're the ones who ask, ‘Does this make sense for our people? Does it help us do better work? Does it reflect the values we say we care about?’ And more often than not, it’s women who are asking those kinds of questions. Think about what that means in a practical sense. When a company is rolling out a new AI writing tool, a male leader might focus on efficiency. A female leader might ask if the tool risks replacing human insight or if it undermines original thinking. Neither approach is wrong. But they lead to different outcomes.” Read more 👉 https://lnkd.in/enqz6jNy ✍️ Article by Dr. Diane Hamilton #WomenInSTEM #GirlsInSTEM #STEMGems #GiveGirlsRoleModels

It's been a whirlwind week of media coverage, with an appearance on CTV Your Morning leading to articles in CTV News, BNN Bloomberg, and Inc. Magazine. I've been talking about the gender gap in AI adoption. 18 global studies covering 140,000+ people revealed that women are 20-25% less likely than men to use GenAI tools at work. Researchers found the gap is nearly universal, and it persists even when access is equal. If this disparity continues, systems will learn from data that under-represent women, widening existing gaps in technology adoption and economic opportunity. The reasons for the gender gap vary. Women have lower familiarity with AI, and are more likely to want training while men "just try it." Women are afraid of being penalized at work for taking a risk with AI tools. As I said in an interview: "A man using emerging technology is called 'innovative.' A woman using emerging tech is 'cheating'. " Women are also concerned about bias in AI outputs. All of this adds up to a confidence gap - not a capability gap - and it slows adoption. If women sit on the sidelines of the AI revolution, they risk falling further behind. Their career growth stagnates, and gender pay inequities grow. I'm particularly interested in AI adoption amongst entrepreneurs. The top reasons why businesses adopt AI are to be more efficient and productive. The Canadian Chamber of Commerce's Business Data Lab says that GenAI could lift Canada’s labour productivity by 6% in the next decade. A report from Microsoft suggests that the average ROI for companies is $3.50 for every $1 invested in AI. If 20-25% of women and gender-diverse entrepreneurs sit out AI adoption, that's billions in GDP that Canada will never see. Even worse, we don't see the economic benefits of women-led businesses. The World Economic Forum says women-led firms are proven 'regenerative forces' - they reinvest locally and create greener, safer jobs. If women and gender-diverse entrepreneurs are left behind on AI, we don't just lose efficiency; we lose the very businesses that knit communities together. This is why I'm proud to be working on the AI Skills Lab Canada program (https://aiskillslab.ca). It's a national, women-led pilot from The Forum, Camp Tech Inc, and Growclass, with co-investment from DIGITAL. The program features free training and support for women, transfemme, and non-binary entrepreneurs to grow their businesses with AI. Our Labs blend short lessons and guided practice on core tools with a responsible AI lens, including data privacy, human-in-the-loop checks, and the Canadian legal context. Our goal is to move participants from awareness to first wins, then surround them with peer and mentor support so they keep going. If you lead, fund, or influence innovation and skills in Canada, this is a moment to act. If you are a gender-diverse entrepreneur, join us. If you already use AI, be a peer champion and show how you work. Let’s close the gap and grow the economy together.

We called it progress. Turns out, it's a wedge. When it comes to AI, women are underrepresented, disproportionately impacted, use it less, and trust it less. Why the World Economic Forum predicts it will take 134 years to close the AI gender gap. How did we create yet another gap 🙄 before AI even got off the ground? Because we haven't closed the previous gaps. Women make up less than 22% of AI professionals globally. In technical roles, that number drops even lower. The gap shows up in models, machines, and money. #️⃣ Data bias: AI models trained on biased data reinforce gender stereotypes, like women linked to nurses, men to CEOs. I read an early study by UNESCO where Llama 2 and ChatGPT were asked to make up stories about women and men. In stories about men, words like "treasure," "woods," "sea," and "adventurous" dominated, while women were more often described with "garden," "love," "gentle," and "husband." Oh, and women were described in domestic roles 4X more often than men. ⚙️ Product design: Virtual assistants are often default female—submissive, helpful, and programmable. We've seen design flaws like this before, like in facial recognition systems that tend to perform worst on black women compared to white men. 💲 Funding: Women-led AI startups receive a fraction of VC funding compared to male-led ones. In fact, only 4% of AI startups are led by women. Then there's disproportionate impact. 80% of jobs will be affected in some way by AI. 57% of jobs susceptible to disruption are held by women compared to 43% of men. If women are anxious, it's because we should be. Women are 1.5X more likely to need to move into new occupations than men due to AI. But we're not anxious about AI just because of its impact on work and jobs; we also don't TRUST it. We know AI algorithms perpetuate bias, and we also know we're more subject to online harm like deepfakes, cyber threats, and fraud. Then there are bigger questions around psychological safety, an altered sense of reality, and social isolation in an increasingly digital world. Sounds like AI is sexist. A literal threat to women -- our livelihood, our social being, our online safety and privacy, our kids. But I don't want to throw it away for all that... ...it's that the most powerful technology claiming to shape our future is being built and deployed by a homogeneous few. This isn't about responsible AI, this is about representation, impact, and responsible humans deciding what to DO with AI. Listen to my conversation with Adriana O'Kain on Mercer's AI-volution podcast. Closing the AI Gender Gap: 🎙️ Spotify: https://lnkd.in/geyp2Scn Apple: https://lnkd.in/g5FamDEJ #FutureOfWork #DigitalDivide #EthicalTech #InclusiveDesign #AI #EquityInTech #HRTech #WomenInTech

I admit it. I got sucked into this trend of asking ChatGPT to generate an image of what it thinks I look like based on what it knows about me. The results? Just as disappointing as every other post I’ve seen shared by a female founder. First, it generated a bearded man. Yes, a man - despite having many months of my data as Virginia Frischkorn, founder and CEO. Even more striking was its explanation: "From your sharp, Type A efficiency to your creative background and presence across Aspen, Denver, and New York - I imagined someone who's polished, confident, approachable, and stylish in an understated way." Apparently, those qualities scream "MUST BE A MAN!" to the algorithm. When I questioned why it assumed I was male, it switched to a brunette woman. Only when I explicitly told it I have blonde hair and blue eyes did it finally create an image that actually could have represented me. What's revealing here isn't just that AI dispenses with the process of asking clarifying questions but the way its default programming favors one story above all: AI sees "founder," "CEO," "Type A efficiency," and "confident" and immediately generates a male image. I had to specifically challenge these assumptions to be seen accurately. This isn't just about AI getting an image wrong. It's about the subtle ways technology reinforces who we expect to see in leadership positions, who "looks like" a founder, and whose stories show up repeatedly front and center. For women founders, entrepreneurs of color, and anyone who doesn't fit the "hoodie-wearing tech bro" stereotype that AI seems wired to double-down on - we're still fighting to be seen as legitimate leaders, even by the technology we help create. The tech we build will only be as inclusive as the data and perspectives that shape it. This is why diverse teams, inclusive datasets, and questioning our assumptions matters so deeply. Has anyone else tried this experiment? What did the AI think you looked like? Sarah Allen Preston Katie Fortunato Katie Dunn Kristen Gendron #femalefounder #ai #diversity

Women who use AI are 'cheaters.'  Men who use AI are 'innovators.'  See the problem? It's the classic double standard. When a woman uses ChatGPT, she might fear being seen as "taking shortcuts." When a man does it, he's "leveraging innovative tools." In a recent Harvard Business School article, researchers show women are adopting AI tools 25% less than men. The research reveals a staggering truth: men are building career advantages with AI while women deliberate ethical concerns, potentially widening existing workplace disparities. Remember when executives first got email? Their assistants (mostly women) managed it while they dictated responses. Now imagine being the last executive to adopt email - that's the career disadvantage at stake with AI. It’s not a unique problem though. Every technological advance faces this pattern: initial resistance followed by universal adoption. From calculators to the Internet to now AI, the early adopters gain the advantage. At Mother AI, our research shows not only is there a gender gap but a massive "parent gap" in AI adoption. (Read the top five reasons for the parent gap in the comments) Working moms are falling even further behind - sacrificing productivity and time gains while shouldering more household management than ever. Ask yourself: If you had a tool that could save hours each week, would you let concerns about "cheating" stop you from using it? What's been your biggest hesitation about trying AI tools? Let's discuss in the comments! #AIAdoption #WomenInTech #MotherAI #ShePowersAI

Women are adopting AI tools at a 25 percent lower rate than men on average. This is according to research by Harvard Business School Associate Professor Rembrand Koning. With my product hat on, I’m curious about why this is. This is “despite the fact that it seems the benefits of AI would apply equally to men and women.” Ok. But is the build designed to address the needs for all… in order to achieve these benefits? Why the gap? The research suggests women are concerned about the ethics of using the tools and may fear they will be judged harshly in the workplace for relying on them. Are these real pain points of women being addressed? A good place to start is at the root, by listening, understanding, and addressing the needs of users. Koning noted: ➡️ Women appear to be worried about the potential costs of relying on computer-generated information, particularly if it’s perceived as unethical or “cheating.” ➡️ Women face greater penalties in being judged as not having expertise in different fields.  They might be worried that someone would think that even though they got the answer right, they ‘cheated’ by using ChatGPT. To design and build for all AND achieve intended outcomes: “It’s important to create an environment in which everybody feels they can participate and try these tools and won’t be judged for [using them],” Koning says. It really comes down to understanding and addressing the real pain points and concerns that women have. #AI #AILiteracy #ProductManagement